🌍 Just completed a full End-to-End Image Classification project on Intel's Natural Scenes Dataset! As a Data Scientist & ML Engineer, I built a complete pipeline that automatically identifies 6 types of natural scenes — Buildings, Forest, Glacier, Mountain, Sea & Street — from raw images. 📌 What I did: ✅ Exploratory Data Analysis (EDA) — class distributions, brightness/contrast stats, color histograms ✅ Data Augmentation — rotation, zoom, flip, brightness tuning to prevent overfitting ✅ Built & compared 4 Deep Learning models: 🔹 Simple CNN (Baseline) 🔹 Deep Custom CNN with BatchNorm Dropout 🔹 VGG16 Transfer Learning (freeze fine-tune) 🔹 MobileNetV2 Transfer Learning ✅ Grad-CAM visualizations — to explain WHAT the model actually sees ✅ Confusion Matrix, Classification Report & Per-Class Accuracy ✅ Final predictions exported as CSV with confidence scores 📊 Dataset: ~25,000 images | 6 classes | 150×150 px 🏆 Best Model Accuracy: 94% 💡 Key Takeaway: Transfer Learning is a game-changer. MobileNetV2 & VGG16 significantly outperformed custom CNNs — and Grad-CAM made the model explainable to non-technical stakeholders. 🚀 If your business needs: → Image classification or object detection solutions → Computer Vision pipelines for automation → Explainable AI for stakeholder reporting Let's connect and talk! 📩 DM me or drop a comment below. #MachineLearning #DeepLearning #ComputerVision #CNN #TransferLearning #ImageClassification #VGG16 #MobileNetV2 #GradCAM #Python #TensorFlow #Keras #DataScience #AI #NeuralNetworks #Kaggle #OpenToWork #MLEngineer #DataScientist #AIFreelancer #ClientWork #Portfolio #BuildInPublic #ArtificialIntelligence #MLOps #ExplainableAI #LinkedInLearning #TechPakistan #PakistaniDeveloper #FreelancePakistan

🔥 XAI Paper Highlight from Make 📝 Using Segmentation to Boost Classification Performance and Explainability in CapsNets 🔗 Read more: mdpi.com/2504-4990/6/3/68 #CapsuleNetworks #Explainability #ImageClassification

Check this newly published article "Strategic Sample Selection in #DeepLearning: A Case Study on #ViolenceDetection Using Confidence-Based Subsets" at brnw.ch/21x1Xp0 Authors: Francisco Primero Primero et al. #mdpisymmetry #imageclassification @TecNM_MX @UAEM_MX

Learn how to build real-world AI systems from the SES – OxML 2026. We’re excited to feature Noor Sajid (Harvard University), who will lead a hands-on session on building a Convolutional Neural Network (CNN) for image classification. Noor brings strong expertise in applied machine learning, with a focus on translating theory into practical, engineering-driven solutions. In this session, you’ll go beyond concepts and actually implement end-to-end pipelines—covering model design, training, and evaluation. 🗓 7–9 & 15–16 May (Online) ⚙️ Hands-on • Engineering-driven • End-to-end AI systems 🚨 Limited slots remaining 🔗 oxfordml.school #MLxCases #OxML #CNN #ImageClassification Noor S.

New tutorial | Image classification with Ultralytics YOLO26 🖼️ Train YOLO26 on the Caltech-256 dataset and evaluate performance using top-1 & top-5 accuracy. Watch here ➡️ bit.ly/3NDkRey #YOLO26 #computervision #imageclassification

How long does it take for an industrial-grade AI camera to learn “object recognition”? #SenseCraft #reCamera: Just 3 minutes. In the field of edge AI, enabling devices to quickly and accurately “recognize” specific objects has always been a core challenge. Today, the SenseCraft AI platform officially announces support for the Recamera series of industrial-grade AI cameras, empowering this high-performance AI camera with robust image classification model training capabilities. #EdgeAI #AIot #ImageClassification

📣 Deal of the Day 📣 Feb 20 HALF OFF new liveProject series! Vision Models for Classification and YOLO Segmentation & selected titles: hubs.la/Q0440C840 For aspiring #machinelearning engineers, #AI-curious developers, and students looking to dive deep into #deeplearning through a fun, real-world project. Help wildlife organizations automatically identify and monitor elephants in images! In this liveProject series, you’ll build a custom CNN to classify Asian vs. African elephants, boost accuracy with transfer learning using #Xception and #MobileNet, and implement #YOLOv8 #segmentation for precise detection and localization. #ImageClassification #TransferLearning #ObjectDetection #NeuralNetworks

Convolutional Neural Network Natural Image Classification System A full-scale CNN pipeline for image classification, from data preprocessing and augmentation to CNN architecture design, training, evaluation, and optimization.#ImageClassification #CNN #DeepLearning #NeuralNetworks

💥Excited for the publication: "Integrating Foundation Model Features into Graph Neural Network and Fusing Predictions with Standard Fine-Tuned Models for #Histology Image Classification" 🔗 shorturl.at/WiwgT 🏫 @DP__University 📌#GraphNeuralNetworkn #ImageClassification

📚 #MachineLearning Models for the Classification of #HistopathologicalImages of #ColorectalCancer 🔗 mdpi.com/2076-3417/14/22/107… 👨‍🔬 by Nektarios Georgiou, Pavlos Kolias and Ioanna Chouvarda 🏫 @Auth_University #imageclassification

Computers can't "see" like us, so how do they recognize things? 🦓🧐 In this episode of Leaps to Learn, Pramesh Gautam, our Principal Engineer, AI, simplifies image classification, the technique that teaches models to identify what's in a picture by learning from labeled data. Think of it as building a computer's visual "brain" by teaching it how to see. 👀🔍 #LeapfrogTechnology #LeapsToLearn #imageclassification #data #AI

🔥 Read our Highly Cited Paper 📚 Unraveling the Impact of Class Imbalance on #DeepLearning Models for Medical #ImageClassification 🔗 mdpi.com/2076-3417/14/8/3419 👨‍🔬 Carlos J. Hellín et al. 🏫 @UAHes / @LivUni #imageanalysis #artificialintelligence #lungpathologies

Finally done with this Dog breed image classification. Its my first ever deep learning project and it gave me insight into the world of deep learning and computer vision. Github link: github.com/Doyinakinloye/Dog…. #Imageclassification #ai #computervision #deeplearning

Day 3 of 40🚀 - Had to fit my model again 'cause runtime disconnected while training it the last time. - Made predictions on the test data. (both took about an hour ) - Learnt a bit about model architecture and activation functions. #40daysofcode #imageclassification #ai

이것도 시작하는데 키워드 놓치긴 아쉽지. @JoinSapien @cookiedotfun Sapien은 혁신적인 분산형 AI 데이터 파운드리로, 인간의 전문지식과 AI 학습을 연결하는 프로토콜임. 쉽게 말해서 어떤 기업이나, AI 모델, 또는 에이전트가 인간의 전문지식을 소싱할 수 있고, 누구나 AI 발전을 위해 자신의 지식을 기여할 수 있는 무허가 프로토콜 주요 키워드 30개 -DecentralizedDataFoundry -HumanInTheLoop -RLHF -DataLabeling -LLMFineTuning -TheForge -PlayToEarn -Gamification -BaseNetwork -PermissionlessProtocol -QualityAssurance -SlashingMechanism -OnchainReputation -TokenEconomics -Crowdsourcing -AITrainingData -Annotation -TextClassification -SentimentAnalysis -ImageClassification -SubjectMatterExpert -Marketplace -ModelEvaluation -SemanticSegmentation -QuestionAnswering -PointsProgram -Stake -Web3Infrastructure -VariantFund -LLM

🔥 Read our Paper 📚 Moving Healthcare AI Support Systems for Visually Detectable Diseases to Constrained Devices 🔗 mdpi.com/2076-3417/14/24/114… 👨‍🔬 by Tess Watt,Christos Chrysoulas,Peter J. Barclay,Brahim El Boudani andGrigorios Kalliatakis. @HeriotWattUni #tinyML #computing #offloading #artificialintelligence #machinelearning #computervision #imageclassification

Train Ultralytics YOLO11 on the ImageNet10 dataset! A small-scale subset of ImageNet is designed for CI tests and quick training pipeline validation, while preserving the original dataset’s structure. Learn more ➡️ ow.ly/BOif50VSnWi #ImageNet10 #ImageClassification #AI

Reading the AlexNet paper this week — the one that introduced deep learning in image classification 🔥 Crazy how an 8-layer CNN changed everything back in 2012. #DeepLearning #CNN #AI #LearnInPublic #AlexNet #researchpaper #Research #ML #WomenInTech #ImageClassification

Coding Grounds: Image classification using ML.NET Machine Learning toreaurstad.blogspot.com/202… #mlnet #dotnet #csharp #ai #azureai #machinelearning #imageclassification #blazorserver

FPGA Implementation of Complex-Valued Neural Network for Polar-Represented Image Classification mdpi.com/1424-8220/24/3/897 #imageclassification #FPGA