Robust Training of Social Media Image Classification Models by Firoj Alam (14158866)

“…Recent advances in computer vision and deep neural networks have enabled the development of models for image classification for a number of tasks, including detecting crisis incidents, filtering irrelevant images, classifying images into specific humanitarian categories, and assessing the severity of the damage. …”

LungVision: X-ray Imagery Classification for On-Edge Diagnosis Applications by Aldamani, Raghad

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Low-Light Image Enhancement for Object Classification using Deep Learning by Al Sobbahi, Rayan

“…We then address a common problem of these models depicted by their design as standalone solutions without focusing on the impact of enhancement on high-level computer vision tasks like object classification. Our review and empirical evaluations show that enhancing LLI visual quality does not necessarily correlate with improved object detection and classification performance, and may even deteriorate it, especially in cases where enhanced images include extreme artifacts. …”
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Secure and Robust Deep Learning Using Homomorphic Encryption and Adversarial Approach for Image Classification by Abbass, Ali

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An IoT System Using Deep Learning to Classify Camera Trap Images on the Edge by Zaulkernan, Imran

“…Raspberry Pi consumed the least average current (838.99 mA) with a ten times worse latency of 2.83 s/image (s.d. = 0.036). Nano was the only reasonable option as an edge device because it could capture most animals whose maximum speeds were below 80 km/h, including goats, lions, ostriches, etc. …”
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Exploring Semi-Supervised Learning Algorithms for Camera Trap Images by Sajun, Ali Reza

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Waste Classification for Sustainable Development Using Image Recognition with Deep Learning Neural Network Models by Meena Malik (17542089)

“…Moreover, it resulted in improvised classifications as a result of fine-tuning over region-wise specific litter images.…”

Image-CNN Based Process Control of Profile by Zeinab, Zeinab Jihad

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Deep Learning-Based Classification of Chest Diseases Using X-rays, CT Scans, and Cough Sound Images by Hassaan Malik (10486121)

“…The proposed DCDD_Net model is trained and evaluated on 20 publicly available benchmark chest disease datasets of CXR, CT scan, and cough sound images. The classification performance of the DCDD_Net is compared with four baseline models, i.e., InceptionResNet-V2, EfficientNet-B0, DenseNet-201, and Xception, as well as state-of-the-art (SOTA) classifiers. …”

A hybrid 3D CNN-LSTM model with soft spatial attention mechanism for accurate hyperspectral image classification by Mohamed Sultan Mohamed Ali (17317003)

“…The results suggested that the proposed model could be applied to various fields, including agriculture, environmental monitoring, and land management, with significant improvements in classification accuracy.…”

Analysing Pneumonia Disease Depending on X-Ray Images of Chest Using Deep Learning by Khamees, Ahmed

“…In this paper, the author aims to review and enhance Image recognition and classification using ML methodologies. …”
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Hybrid Neural Networks for Precise Hydronephrosis Classification Using Deep Learning by Abdus Salam (1918387)

“…</p><h3 dir="ltr">Conclusion</h3><p dir="ltr">This study presents an automated, objective pipeline for analyzing renal ultrasound images. The proposed framework supports high segmentation accuracy and reliable classification, facilitating standardized and reproducible hydronephrosis assessment. …”

Dual-stage segmentation and classification framework for skin lesion analysis using deep neural network by Khadija Manzoor (22565369)

“…Experiments were conducted on three benchmark datasets: Human against machine with 10,000 training images (HAM10000), International Skin Imaging Collaboration (ISIC) 2018, and the newly released ISIC 2024 SLICE-3D dataset. …”

Evaluation of Neuro Images for the Diagnosis of Alzheimer's Disease Using Deep Learning Neural Network by Ahila A (18394806)

An Integrated Design for Classification and Localization of Diabetic Foot Ulcer Based on CNN and YOLOv2-DFU Models by Javaria Amin (14557730)

“…In the classification phase, deep features are extracted and supplied to the number of classifiers such as KNN, DT, Ensemble, softmax, and NB to analyze the classification results for the selection of best classifiers. …”

Cancerous and Non-Cancerous MRI Classification Using Dual DCNN Approach by Zubair Saeed (19325647)

“…Unlike traditional machine learning methods requiring manual feature extraction, DL models are adept at handling complex data like MRIs and excel in classification tasks, making them well-suited for medical image analysis applications. …”

Pavement Crack Assessment Using Satellite Remote Sensing and Deep Learning Model by Al Adab, Maryam

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Intelligent Fusion of Deep Features for Improved Waste Classification by Kashif Ahmad (12592762)

“…<p dir="ltr">In this article, we address the problem of an image-based automatic classification of waste materials. …”

A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata by Siddiqui, Ansah Juned

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A novel method for the detection and classification of multiple diseases using transfer learning-based deep learning techniques with improved performance by Krishnamoorthy Natarajan (22047464)