Deep Learning Jobs

I have a custom-built X-ray system dedicated to mango grading. The control electronics expose a Python API that streams 16-bit radiographic frames at conveyor speed and can fire an air-jet gate on command. What I need next is a production-ready program that • ingests each frame in real time, • detects spongy, internally damaged or otherwise bad fruit with high precision, and • sends the gate signal fast enough to remove the defect before the next fruit arrives. You are free to design the detection pipeline—classical CV with OpenCV or a small CNN in TensorFlow/PyTorch—as long as it runs on the on-board GPU (NVIDIA Jetson Xavier) and meets the timing budget of 60 ms per fruit. I will supply a labelled image set of good vs. spongy mangoes for training and a li...

I am looking for a highly accurate and detail-oriented data annotator to review, correct, and finalize a dataset of 7,525 satellite images. This batch is part of a broader research dataset of over 12,000 images utilized to assess the Urban Green Space Index in regions like Qassim and Madinah. The current dataset is already in YOLO format, but contains unacceptable labeling errors that must be systematically fixed. The final output must be 100% accurate, strictly formatted, and ready to plug directly into our deep learning training pipeline. Scope of Work & Technical Requirements: Review & Correct: Carefully examine 7,525 PNG images and their corresponding YOLO TXT annotation files. You will adjust, add, or delete bounding boxes to ensure every piece of vegetation is accurately c...

We are developing a next-generation AI-powered dating platform focused entirely on intelligent compatibility matching instead of traditional swipe-based dating. Most dating apps rely on random swipes and superficial filtering, which often leads to low-quality matches. Our platform aims to solve this problem using Artificial Intelligence to deeply understand users and connect them with highly compatible partners. The system will analyze user personality, interests, behavior patterns, lifestyle preferences, and relationship goals to generate AI-driven compatibility matches. The goal is to create a smarter, more meaningful dating experience where users meet people who genuinely align with them. AI Matching Concept The platform will use AI algorithms to evaluate compatibility between us...

I run a fully custom React JS platform that presents investment dashboards to our users. I now need the site to pull live security-market data—specifically stock prices, detailed company financials, and the complete annual and quarterly reports for every covered company to summarize the data—directly from the Corporate data API provider we license. The task breaks down into two connected pieces: 1) API hookup • Authenticate against the vendor’s security market corporate API. • Build efficient React-friendly service calls (REST or GraphQL, whichever the API supports) that return stock prices, financial statements, and the full text of 10-K / 10-Q-style filings. • Cache or paginate data so pages stay fast even when a user requests multiple compani...

My deep-learning solution is already engineered and documented; what I still need is a clean, publication-ready architecture diagram that captures every layer and data flow exactly as specified. I will share detailed notes and sketches outlining inputs, processing blocks, and model components—your task is to translate them into a clear visual delivered as a high-resolution PNG. Accuracy matters more than artistic flair: every connection, tensor shape, and processing step must mirror the design I provide so the diagram can be dropped straight into our technical report. A short clarification call or chat at the start will let us agree on layout conventions (colors, fonts, arrow styles). One round of revisions is included to polish alignment and labelling. Deliverables • Final ...

I need a full-length research paper prepared and shepherded through publication in a Scopus-indexed Q2 journal. The topic is neural-network-based detection of visual defects in woven or knitted textiles, implemented in Python. I am flexible about the framework—TensorFlow, PyTorch, Keras or a comparable library is fine—so long as the final code is reproducible and well-commented. The paper must include a solid literature review, a clearly explained network architecture, an experimental section using a representative dataset of fabric images, and a results discussion that meets the methodological rigour typical of Q2 outlets. I will supply any proprietary images I have; if additional public datasets are needed, please curate them. Deliverables • Draft manuscript formatte...

I am preparing a full-length research article on automated fabric defect detection in industrial environments, driven by convolutional or hybrid neural networks coded in Python with TensorFlow or PyTorch. The end goal is a manuscript ready for submission to a Q2 Scopus-indexed journal, followed through peer-review until final acceptance. What I need from you • Curate or locate a high-quality, publicly shareable dataset (or assemble one from open sources) that covers common textile defects in varied lighting and weave patterns. • Design, train, and tune an appropriate neural-network architecture; document every experiment so the methodology section is fully reproducible. • Produce clear performance analyses—confusion matrices, precision-recall curves, ablation st...

I need a comprehensive dataset to train a CNN algorithm for detecting patient-ventilator asynchronies (PVA). The data should be synthetically generated using Python. Dataset Requirements: - Types of Asynchronies: Trigger asynchrony, Flow asynchrony, Cycle asynchrony - Necessary Details: Occurrence frequency, Patient demographic info Ideal Skills and Experience: - Proficiency in Python - Experience in data synthesis and manipulation - Familiarity with CNNs and dataset requirements for machine learning - Background in medical data or ventilator mechanics is a plus Please ensure the dataset is large and varied enough for effective training.

Necesito producir un vídeos híper realista generado con IA en el que aparezca una persona virtual que hable y presente información de manera fluida y natural. El objetivo principal es crear “Vídeos IA”, así que busco un resultado impactante y creíble que pueda usarse directamente, sin parecer animación ni CGI evidente. Qué requiero • Un rostro o cuerpo completo ultra realista que se mueva y gesticule como una persona real. • Sincronización labial perfecta con la narración en español. • Duración aproximada y guion los definiremos juntos, pero estimo entre 30 s y 2 min. • Entrega final en MP4 4K, además del archivo editable o proyecto fuente. • Derechos...

Work Type: Remote (U.S. only) Employment Type: Contract Compensation: $30–$50 per hour (depending on experience) Start Date: Immediate — Project begins next week We are looking for a skilled AI / ML Engineer to join our team and help build a high-accuracy biometric authentication system for a smart lock platform. The goal of this project is to develop a facial recognition system with extremely low False Acceptance Rate (FAR < 0.01%), capable of identifying users accurately—even in challenging cases such as distinguishing identical twins. Project Environment - Training with large-scale biometric datasets such as MegaFace and mobile face recognition datasets - Deployment architecture will be hybrid, supporting both edge devices (smart lock hardware) and cloud s...

Project Title: Deep Learning Project for Chest X-ray Diagnosis (Edge & Multi-Modal ) Description: I need help implementing a research project on chest X-ray disease detection using deep learning. The project should include: Dataset preprocessing (MIMIC-CXR / CheXpert) CNN baseline model (ResNet) Lightweight model (MobileNetV3 or similar) Multi-modal input (X-ray images + patient metadata) Basic edge optimization (model size, inference speed) Continual / adaptive learning simulation Evaluation metrics (Accuracy, AUC, F1-score, Precision, Recall) Result tables and graphs for research

I am conducting advanced research in machine learning and artificial intelligence, with interests that include Graph Neural Networks, deep learning, and data-driven modeling. I am seeking an experienced machine learning / deep learning research assistant to collaborate on preparing two experimental journal manuscripts for submission to Scopus-indexed Q2 or Q3 journals. The role involves supporting the research and manuscript preparation process. All work must follow standard academic integrity and publication ethics. ⸻ Scope of Work The assistant will help with: • Literature review on recent machine learning and deep learning methods • Supporting experimental design and benchmarking • Assisting with implementation and experiments (Python / PyTorch / TensorFlow preferred)...

I have an iOS fractal explorer written in Swift that uses Metal for GPU rendering. It already implements a deep-zoom Mandelbrot path based on perturbation and float-float style precision splitting (reference orbit + shader-side deltas). At moderate zoom levels the app behaves well, but beyond roughly 1e5 magnification the two Mandelbrot paths begin to fail in different ways: - The normal Mandelbrot renderer becomes visibly pixelated and resolution-limited. - The deep Mandelbrot renderer based on perturbation does not merely become pixelated; instead, it starts to lose fine structural detail. Regions that should contain rich micro-structure turn into flat, smoothed, or incorrect-looking areas, sometimes with visible tile artefacts. During continuous zooming and panning, performance also d...

I need help to reduce overfitting in my hybrid vision transformers/CNN model for prostate cancer classification. Current setup: - Training on medium resolution image data - Data augmentation applied, but only one technique Ideal skills and experience: - Strong background in deep learning, especially with vision transformers and CNNs - Expertise in image data processing and augmentation techniques - Experience with model optimization and overfitting reduction

Title: Create a Custom Sign Language Image Dataset (Alphabets, Numbers, and 20 Word Gestures) Project Overview I am developing a computer vision model that recognizes complete sign language gestures, including alphabet signs, number signs, and common word gestures. To train the model, I need a custom image dataset of sign language gestures captured as still images. The dataset should use one consistent sign language system (for example, American Sign Language – ASL). Please specify which sign language you will use. Only images are required. No video is needed. Dataset Requirements The dataset should include: 26 alphabet signs (A–Z) 10 number signs (0–9) 20 common word gestures Total gesture classes: 56 gesture classes Example word gestures may include: hello thank_you ple...

Project Overview: I am seeking a highly skilled n8n Automation Expert to develop and deploy a sophisticated, end-to-end content generation engine on my own n8n instance. The goal is to automate SEO-optimized article writing, AI image creation, and multi-platform social media distribution while using Google Sheets as a central database for content management and duplication prevention. Required Workflow & Technical Logic: Smart Trigger & Duplicate Prevention (Google Sheets): The workflow must run on a Cron Job (scheduled). Before generating any content, the system must query a specific Google Sheets file to ensure the topic or title has not been used previously. After a successful run, the workflow must append the new Title, Date, and WordPress Post URL to the sheet to prevent ...

We are conducting a research project in Geospatial Artificial Intelligence and Remote Sensing that supports an academic manuscript submission to journals such as: ISPRS International Journal of Geo-Information IEEE Journal of Selected Topics in Applied Earh Observations and Remote Sensing The system integrates: Satellite image processing Computer vision object detection Large Language Model (LLM) enrichment Retrieval-Augmented Generation (RAG) The engineering system already exists. Your role is to design and execute rigorous ML experiments and evaluation pipelines to support publication-quality results. Infrastructure and deployment will be handled by a DevOps engineer. System Architecture The pipeline is based on the AWS open-source geospatial processing framework: OSML ModelRunner Refer...

I need software that detects temperature gradients in stitched, high-resolution images. Requirements: - Analyze thermal images, focusing on temperature gradients. - Generate detailed reports on detected anomalies. - Input format: RJPG. Ideal Skills: - Experience in image processing and thermal analysis. - Proficiency in software development for anomaly detection. - Knowledge of report generation based on image data. Please include relevant experience in your application.

I am commissioning a 60–70 page dissertation on “Detection of deep-fake images and videos (including voice modulation) using AI.” Academic presentation is essential; please apply a formal scholarly layout with in-text citations and a full reference list. I am flexible on the exact style (APA, MLA, Chicago) as long as it is applied consistently and meets university standards. Research approach I only need a thorough, critical literature review—no primary experiments or case studies. The writing should synthesise current peer-reviewed work on computer-vision techniques, GAN identification, forensic audio analysis, multimodal fusion, and emerging AI counter-measures, weaving these strands into a cohesive argument that highlights research gaps and future directi...

We are conducting a research project in Geospatial Artificial Intelligence and Remote Sensing that supports an academic manuscript submission to journals such as: ISPRS International Journal of Geo-Information IEEE Journal of Selected Topics in Applied Earh Observations and Remote Sensing The system integrates: Satellite image processing Computer vision object detection Large Language Model (LLM) enrichment Retrieval-Augmented Generation (RAG) The engineering system already exists. Your role is to design and execute rigorous ML experiments and evaluation pipelines to support publication-quality results. Infrastructure and deployment will be handled by a DevOps engineer. System Architecture The pipeline is based on the AWS open-source geospatial processing framework: OSML ModelRunner Refer...

The project is a short series of adult videos in which I need the actress’s face replaced with that of a fictional character I generated with AI. The finished footage must look completely authentic—skin tones, lighting, eye-line, micro-expressions, everything—so a photorealistic approach is essential. All raw 4K source scenes are ready to share. I also have a base model of the character’s face; however, the dataset still needs polishing before training. I’ll rely on you to refine that set, handle training, and composite the swap seamlessly back into the footage. Tools such as DeepFaceLab, FaceSwap, or your preferred deep-learning pipeline are fine, provided the final output holds up at full resolution without uncanny artifacts. Subtle colour grading or mino...

**Project Title:** Personalized Recommendation System Using Collaborative Filtering and Deep Learning **Project Description:** I am looking for an experienced AI,ML,DL developer to build a personalized recommendation system using collaborative filtering and deep learning techniques. The system should analyze user–item interaction data and generate personalized recommendations for users. **Project Objectives:** * Develop a recommendation model using collaborative filtering. * Integrate deep learning techniques (such as Neural Collaborative Filtering). * Improve recommendation accuracy by capturing complex user–item relationships. * Generate Top-N personalized recommendations. **Scope of Work:** 1. Data preprocessing and creation of a user–item interaction matrix. 2. I...

Necesito crear una plataforma digital capaz de generar avatares hiperrealistas partiendo de fotografías y grabaciones de voz de cada usuario. El objetivo es que el avatar sea virtualmente indistinguible de la persona real: expresiones faciales naturales, sincronización labial exacta con la voz suministrada y movimientos corporales fluidos. Uso previsto El producto final vivirá dentro de una plataforma propia; por tanto, todo el flujo —desde la carga de datos hasta la interacción final— debe integrarse de forma transparente. Funcionalidades clave que requiero incorporar: • Carga de fotos y grabaciones de voz directamente en la plataforma. • Personalización avanzada de rasgos faciales y expresiones para que cada usuario refine ...

sixteen 1、 Title: Research on Partial Discharge Fault Diagnosis Method for Power Substation Based on Combinatorial Logic and Deep Belief Network 2、 Journal Division: SCI Zone 4 I need you to match 3-5 journals based on my topic, and I may submit them based on the journals you provide me with in the future, 3、 Writing requirements: Write according to my paper title and journal requirements, and provide necessary journal requirements documents, including an AI plagiarism report Turnitin (Artificial Intelligence) (1) Word count: 5000-8000 words (2) Formulas and symbols: cannot exist in image format, nor can they be created using Word's formula editor. Please format all formulas using MathType to ensure that the font and size match the text. (3) Formula number: All formulas must be number...

Hello, I am a researcher looking for a Python developer specialized in Artificial Intelligence to implement the programming part of an innovative project idea. I am looking for someone able to: develop the algorithm in Python process and analyze data build a functional prototype contribute to the technical implementation of the project Required profile: serious, competent, reliable, with strong skills in Python and AI. Possibility of long-term collaboration depending on the results. Best regards.

I want to see a working proof-of-concept that can watch a live webcam feed in an indoor setting and reliably decide whether someone is merely holding a phone or actively using it. The prototype must process the video stream in real time, recognise the presence of a smartphone, then look for behavioural cues—hand placement, posture and, ideally, gaze direction—to confirm active usage. Whenever the model judges that the phone is being used, it should trigger an audible or visible alarm on the host machine instantly; no other logging or alert channels are required for this first iteration. I am happy for you to choose your preferred computer-vision stack (e.g. OpenCV, MediaPipe, PyTorch, TensorFlow, ONNX) as long as the end result runs on a typical workstation without specia...

I’m finalising an academic paper that relies heavily on recent advances in Deep Learning, and I need a polished Literature Review and Background section to anchor the study. The review must cover three focal points: • Vision Transformers (ViTs) • Graph Convolution Networks (GCNs) • Convolutional Neural Networks (CNNs) I already have an outline of my methodology and results; what’s missing is a cohesive narrative that traces how these architectures evolved, the key papers that shaped them, and the open questions my work addresses. Your job is to survey and synthesise the state-of-the-art, cite peer-reviewed sources (preferably within the last five years unless historically significant), and weave the material into a clear, publication-ready section. IEEE...

I need a YOLOv8 model trained to detect and classify approximately 12 types of fishing vessels from provided images. The dataset will be in YOLO/COCO format. Requirements: - Target accuracy: ~90%+ - Input image resolution: 1280x1280 - Performance metrics: Precision, Recall, F1 Score - Inference optimization: Balanced between speed and accuracy Deliverables: - Trained weights (.pt) - Training script - Inference code Ideal Skills & Experience: - Expertise in YOLOv8 and PyTorch - Experience with object detection and model training - Familiarity with performance metrics and optimization techniques

The project centers on building a production-ready TensorFlow 2.x model that classifies tabular data delivered to us through an internal API. I have the API specifications and sample payloads ready; you will turn those streams into a clean training pipeline, engineer the right features, and iterate until the classifier meets our performance targets in real-world tests. Scope of work • Data pipeline – pull the API data, handle preprocessing, and produce TensorFlow-friendly datasets for train/val/test splits. • Model development – design, train, and tune a deep learning architecture suitable for tabular inputs (e.g., wide & deep, Transformer, or other proven structures). • Optimization – experiment with hyperparameters, regularization, and callback...