Computer Vision and Image Analysis for Industry 4.0
portes grátis
Computer Vision and Image Analysis for Industry 4.0
Dewan, M. Ali Akber; Ahad, Md Atiqur Rahman; Siddique, Nazmul; Arefin, Mohammad Shamsul
Taylor & Francis Ltd
12/2024
197
Mole
9781032187624
Pré-lançamento - envio 15 a 20 dias após a sua edição
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A Benchmark Dataset for Document Level Offline Bangla Handwritten Text Recognition (HTR) and Line Segmentation. 2. A New Approach Using Convolutional Neural Network for Crops and Weeds Classification. 3. Lemon Fruits Detection and Instance Segmentation Under Orchard Environment Using Mask R-CNN and YOLOv5. 4. A Deep Learning Approach in Detailed Fingerprint Identification. 5. Probing Skin Lesions and Performing Classification of Skin Cancer Using Efficient Net while Resolving Class Imbalance Using SMOTE. 6. Advanced Grad CAM: Improved Visual Explanations of CNN's decision in Diabetic Retinopathy. 7. Bangla Sign Language Recognition Using Concatenated BDSL Network. 8. Chest Xray Net: A Multi-class Deep Convolutional Neural Networks for Detecting Abnormalities in Chest X-Ray Images. 9. Achieving Human Level Performance on the Original Omniglot Challenge. 10. A Real-Time Classification Model for Bengali Character Recognition in Air-Writing. 11. A Deep Learning Approach for Covid-19 Detection in Chest X-Rays. 12. Automatic Image Captioning Using Deep Learning. 13. A Convolutional Neural Network Based Approach to Recognize Bangla Handwritten Characters. 14. Flood Region Detection Based on K-Means Algorithm and Color Probability. 15. Fabrication of Smart Eye Controlled Wheelchair for Disabled Person.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Computer vision;image analysis;Industry 4.0;Deep learning;Bangla NLP;Max Pooling Layers;CNN Model;Convolutional Layers;Roc Curve;Chest X-ray Images;Bangla Characters;Deep Convolutional Neural Network;F1 Score;Pre-trained Model;Convolution Layers;NPDR.;Line Segmentation;Data Set;Minority Class Samples;Deep Neural Network Model;Severe NPDR;Reference Translation;MNIST Dataset;50th Epoch;Five-fold Cross-validation Method;Flood Detection;Skin Lesion Images;Connected Component Labelling;Rt PCR Test;Scentless Mayweed
A Benchmark Dataset for Document Level Offline Bangla Handwritten Text Recognition (HTR) and Line Segmentation. 2. A New Approach Using Convolutional Neural Network for Crops and Weeds Classification. 3. Lemon Fruits Detection and Instance Segmentation Under Orchard Environment Using Mask R-CNN and YOLOv5. 4. A Deep Learning Approach in Detailed Fingerprint Identification. 5. Probing Skin Lesions and Performing Classification of Skin Cancer Using Efficient Net while Resolving Class Imbalance Using SMOTE. 6. Advanced Grad CAM: Improved Visual Explanations of CNN's decision in Diabetic Retinopathy. 7. Bangla Sign Language Recognition Using Concatenated BDSL Network. 8. Chest Xray Net: A Multi-class Deep Convolutional Neural Networks for Detecting Abnormalities in Chest X-Ray Images. 9. Achieving Human Level Performance on the Original Omniglot Challenge. 10. A Real-Time Classification Model for Bengali Character Recognition in Air-Writing. 11. A Deep Learning Approach for Covid-19 Detection in Chest X-Rays. 12. Automatic Image Captioning Using Deep Learning. 13. A Convolutional Neural Network Based Approach to Recognize Bangla Handwritten Characters. 14. Flood Region Detection Based on K-Means Algorithm and Color Probability. 15. Fabrication of Smart Eye Controlled Wheelchair for Disabled Person.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Computer vision;image analysis;Industry 4.0;Deep learning;Bangla NLP;Max Pooling Layers;CNN Model;Convolutional Layers;Roc Curve;Chest X-ray Images;Bangla Characters;Deep Convolutional Neural Network;F1 Score;Pre-trained Model;Convolution Layers;NPDR.;Line Segmentation;Data Set;Minority Class Samples;Deep Neural Network Model;Severe NPDR;Reference Translation;MNIST Dataset;50th Epoch;Five-fold Cross-validation Method;Flood Detection;Skin Lesion Images;Connected Component Labelling;Rt PCR Test;Scentless Mayweed
