UnionCAM: enhancing CNN interpretability through denoising, weighted fusion, and selective high-quality class activation mapping by Hao Hu, Hao Hu, Rui Wang, Hao Lin, Huai Yu

“…Deep convolutional neural networks (CNNs) have achieved remarkable success in various computer vision tasks. …”
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High-precision lung cancer subtype diagnosis on imbalanced exosomal data via Exo-LCClassifier by Siyu Zhan, Siyu Zhan, Hao Yu, Shuang Liu, Ke Qin, Lu Guo

“…This study aims to address these challenges by proposing an innovative deep learning-based method for predicting lung cancer subtypes.MethodsWe propose a method called Exo-LCClassifier, which integrates feature selection, one-dimensional convolutional neural networks (1D CNN), and an improved Wasserstein Generative Adversarial Network (WGAN). …”
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Dynamic Optimization of Recurrent Networks for Wind Speed Prediction on Edge Devices by Laeeq Aslam, Runmin Zou, Ebrahim Shahzad Awan, Sayyed Shahid Hussain, Muhammad Asim, Samia Allaoua Chelloug, Mohammed A. ELAffendi

“…To address this gap, we propose a framework that co-optimizes the discrete hyperparameter spaces of Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU) and Temporal Convolutional Network (TCN) models under strict memory constraints. …”
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TCL: Time-Dependent Clustering Loss for Optimizing Post-Training Feature Map Quantization for Partitioned DNNs by Oscar Artur Bernd Berg, Eiraj Saqib, Axel Jantsch, Irida Shallari, Silvia Krug, Isaac Sanchez Leal, Mattias O'Nils

“…The proposed framework offers a scalable solution for deploying high-performance AI models on IoT devices, extending the feasibility of real-time inference in resource-constrained environments.…”
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A Novel Dual-Modal Deep Learning Network for Soil Salinization Mapping in the Keriya Oasis Using GF-3 and Sentinel-2 Imagery by Ilyas Nurmemet, Yang Xiang, Aihepa Aihaiti, Yu Qin, Yilizhati Aili, Hengrui Tang, Ling Li

“…DMSSNet incorporates self-attention mechanisms and a Convolutional Block Attention Module (CBAM) within a hierarchical fusion framework, enabling the model to capture both intra-modal and cross-modal dependencies and to improve spatial feature representation. …”
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Nystromformer based cross-modality transformer for visible-infrared person re-identification by Ranjit Kumar Mishra, Arijit Mondal, Jimson Mathew

“…To address this, we propose NiCTRAM: a Nyströmformer-based Cross-Modality Transformer designed for robust VIS-IR person re-identification. Our framework begins by extracting hierarchical features from both RGB and IR images through a shared convolutional neural network (CNN) backbone, ensuring the preservation of modality-specific characteristics. …”
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SCL-YOLOv11: A Lightweight Object Detection Network for Low-Illumination Environments by Shulong Zhuo, Hao Bai, Lifeng Jiang, Xiaojian Zhou, Xu Duan, Yiqun Ma, Zihan Zhou

“…Furthermore, a lightweight detail-enhancement convolution layer and a shared-convolution detection head are designed to improve the model’s capability in capturing fine-grained details. …”
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Wi-FiAG: Fine-Grained Abnormal Gait Recognition via CNN-BiGRU with Attention Mechanism from Wi-Fi CSI by Anming Dong, Jiahao Zhang, Wendong Xu, Jia Jia, Shanshan Yun, Jiguo Yu

“…Specifically, we propose a deep learning-based framework for multi-class abnormal gait recognition, comprising three key modules: data collection, data preprocessing, and gait classification. …”
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Deep Learning-Based Coding Strategy for Improved Cochlear Implant Speech Perception in Noisy Environments by Billel Essaid, Hamza Kheddar, Noureddine Batel, Muhammad E. H. Chowdhury

“…The second strategy builds on this framework by additionally incorporating bidirectional gated recurrent units (Bi-GRU) alongside TCN and MHA layers, further refining sequence modeling and enhancing noise reduction. …”
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An Explainable Bayesian TimesNet for Probabilistic Groundwater Level Prediction by Zechen Peng, Shaoxing Mo, Alexander Y. Sun, Jichun Wu, Xiankui Zeng, Miao Lu, Xiaoqing Shi

“…BTimesNet transforms 1D time series data into 2D matrices based on periodicity, enhancing the capture of temporal patterns through convolutional filters. A Bayesian framework using Stein Variational Gradient Descent is implemented to quantify predictive uncertainties. …”
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The Robust Vessel Segmentation and Centerline Extraction: One-Stage Deep Learning Approach by Rostislav Epifanov, Yana Fedotova, Savely Dyachuk, Alexandr Gostev, Andrei Karpenko, Rustam Mullyadzhanov

“…The proposed end-to-end framework directly predicts the centerline as a polyline with real-valued coordinates, thereby eliminating the need for post-processing steps commonly required by previous methods that infer centerlines either implicitly or without ensuring point connectivity. …”
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Forecasting Electric Vehicle Charging Demand in Smart Cities Using Hybrid Deep Learning of Regional Spatial Behaviours by Muhammed Cavus, Huseyin Ayan, Dilum Dissanayake, Anurag Sharma, Sanchari Deb, Margaret Bell

“…This study presents a novel predictive framework for estimating electric vehicle (EV) charging demand in smart cities, contributing to the advancement of data-driven infrastructure planning through behavioural and spatial data analysis. …”
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A Dual-Stream Deep Learning Architecture With Adaptive Random Vector Functional Link for Multi-Center Ischemic Stroke Classification by Mahesh Anil Inamdar, Anjan Gudigar, U. Raghavendra, Massimo Salvi, Raja Rizal Azman Bin Raja Aman, Nadia Fareeda Muhammad Gowdh, Izzah Amirah Binti Mohd Ahir, Mohd Salahuddin Bin Kamaruddin, Khairul Azmi Abdul Kadir, Filippo Molinari, Ajay Hegde, Girish R. Menon, U. Rajendra Acharya

“…We demonstrate the strong generalization capabilities of the proposed framework by achieving 92.42% accuracy on a diverse, multi-center dataset of 7,842 CT images. …”
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Clinical Applicability and Cross-Dataset Validation of Machine Learning Models for Binary Glaucoma Detection by David Remyes, Daniel Nasef, Sarah Remyes, Joseph Tawfellos, Michael Sher, Demarcus Nasef, Milan Toma

“…These findings highlight the importance of proper evaluation frameworks, including external validation, to ensure the reliability of artificial intelligence tools for clinical use. …”
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Mechanism of Influence of Spatial Perception on Residents’ Emotion in Child-Friendly Urban Streets of Fuzhou City by Shaofeng CHEN, Zhengyan CHEN, Yuhan XU, Zheng DING

“…Three machine learning architectures are deployed: CNN-BiLSTM Hybrid Model, FCN-RF Semantic Segmentation, and XGBoost-SHAP Interpretability Framework. For FCN-RF Semantic Segmentation, street view images are processed by fully convolutional networks to quantify 10 spatial metrics, validated against human-scored safety perceptions via random forest-based adversarial training; for XGBoost-SHAP Interpretability Framework, the nonlinear relationships between 12 street environment indicators and emotional indices are modeled through extreme gradient boosting, with SHapley additive explanations (SHAP) decoding feature contributions and interaction effects. …”
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Aided Greenway Design Approach Based on Internet Big Data and AIGC Fine-Tuning Model by Yifan WU, Lu MENG, Liang LI

“…The research takes greenways as a typical example to verify the performance of the approach framework. Image and text data related to Beijing greenways from 2013 to 2022 are collected from Weibo platform as the original dataset. …”
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Socializing AI: Integrating Social Network Analysis and Deep Learning for Precision Dairy Cow Monitoring—A Critical Review by Sibi Chakravathy Parivendan, Kashfia Sailunaz, Suresh Neethirajan

“…We describe the transition from manual, observer-based assessments to automated, scalable methods using convolutional neural networks (CNNs), spatio-temporal models, and attention mechanisms. …”
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Artificial Intelligence Models for Pediatric Lung Sound Analysis: Systematic Review and Meta-Analysis by Ji Soo Park, Sa-Yoon Park, Jae Won Moon, Kwangsoo Kim, Dong In Suh

“…Risk of bias was assessed using a modified Quality Assessment of Diagnostic Accuracy Studies (version 2) framework. Data were extracted on study design, dataset, ML methods, feature extraction, and classification tasks. …”
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A Predictive Method for Greenhouse Soil Pore Water Electrical Conductivity Based on Multi-Model Fusion and Variable Weight Combination by Jiawei Zhao, Peng Tian, Jihong Sun, Xinrui Wang, Changjun Deng, Yunlei Yang, Haokai Zhang, Ye Qian

“…Importantly, it provides agricultural researchers and greenhouse managers with a deployable and generalizable framework for digital, precise, and intelligent management of soil water and nutrients in protected horticulture systems.…”
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Channel and Spatial Attention in Chest X-Ray Radiographs: Advancing Person Identification and Verification with Self-Residual Attention Network by Hazem Farah, Akram Bennour, Neesrin Ali Kurdi, Samir Hammami, Mohammed Al-Sarem

“…For the network backbone, a self-residual attention block (SRAB) was implemented within a ResNet50 framework, forming a Siamese network trained with triplet loss to improve feature embedding for identity identification and verification. …”
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