A Framework for Optimizing Deep Learning-Based Lane Detection and Steering for Autonomous Driving by Daniel Yordanov, Ashim Chakraborty, Md Mahmudul Hasan, Silvia Cirstea

“…This project aims to provide a novel framework for optimizing a self-driving vehicle that can detect lanes and steer accordingly. …”
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Integrating Kolmogorov–Arnold Networks with Time Series Prediction Framework in Electricity Demand Forecasting by Yuyang Zhang, Lei Cui, Wenqiang Yan

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Revolutionizing Alzheimer’s disease detection with a cutting-edge CAPCBAM deep learning framework by Houmem Slimi, Sabeur Abid, Mounir Sayadi

“…While the integration of deep learning techniques for AD classification is not entirely new, this study introduces CAPCBAM—a framework that extends prior approaches by combining Capsule Networks with a Convolutional Block Attention Module (CBAM). …”
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Enhancing urban air quality prediction using time-based-spatial forecasting framework by Shrikar Jayaraman, Nathezhtha T, Abirami S, Sakthivel G

“…The proposed Time-Based-Spatial (TBS) forecasting framework is integrated with spatial and temporal information using machine learning techniques on data collected from a wide range of cities. …”
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LumiLoc: A Low-Light-Optimized Visual Localization Framework for Autonomous Drones by Ruokun Qu, Zhiyuan Wang, Yelu Liu, Chenglong Li, Hui Jiang, Chen Fang

“…To address these issues, we propose a low-light-optimized visual localization framework that integrates an attention-based image enhancement module, a robust feature extraction network tailored for degraded environments, and a lightweight pose estimation algorithm that fuses geometric and convolutional features. …”
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CoroYOLO: a novel colorectal cancer detection method based on the Mamba framework by Wenfei Chen, Fengrui Hou, Yika Shen

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Terrain and Atmosphere Classification Framework on Satellite Data Through Attentional Feature Fusion Network by Antoni Jaszcz, Dawid Połap

“…The proposed classifier architecture is the main element of the modeled framework for satellite data analysis, which is based on the possibility of training depending on the client’s desire. …”
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A Spectral Interpretable Bearing Fault Diagnosis Framework Powered by Large Language Models by Panfeng Bao, Wenjun Yi, Yue Zhu, Yufeng Shen, Haotian Peng

“…In this work, we present a novel, interpretable fault diagnosis framework that integrates spectral feature extraction with large language models (LLMs). …”
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eUF: A framework for detecting over-the-air malicious updates in autonomous vehicles by Anam Qureshi, Murk Marvi, Jawwad Ahmed Shamsi, Adnan Aijaz

“…For enhancing security, we incorporate convolutional neural network (CNN) in the uptane framework. …”
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Machine learning frameworks to accurately estimate the adsorption of organic materials onto resin and biochar by Raouf Hassan, Mohammad Reza Kazemi

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A Unified Machine Learning Framework for Li-Ion Battery State Estimation and Prediction by Afroditi Fouka, Alexandros Bousdekis, Katerina Lepenioti, Gregoris Mentzas

“…This paper presents a unified, modular, and extensible machine learning (ML) framework designed to address the heterogeneity and complexity of battery state prediction tasks. …”
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SBCS-Net: Sparse Bayesian and Deep Learning Framework for Compressed Sensing in Sensor Networks by Xianwei Gao, Xiang Yao, Bi Chen, Honghao Zhang

“…To address these challenges, this paper proposes SBCS-Net. This framework innovatively expands the iterative process of sparse Bayesian compressed sensing using convolutional neural networks and Transformer. …”
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FingerDTA: A Fingerprint-Embedding Framework for Drug-Target Binding Affinity Prediction by Xuekai Zhu, Juan Liu, Jian Zhang, Zhihui Yang, Feng Yang, Xiaolei Zhang

“…Artificial intelligence methods, such as Convolutional Neural Network (CNN), are widely used to facilitate new drug discovery. …”
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Implementation of Automatic Segmentation Framework as Preprocessing Step for Radiomics Analysis of Lung Anatomical Districts by Alessandro Stefano, Fabiano Bini, Nicolò Lauciello, Giovanni Pasini, Franco Marinozzi, Giorgio Russo

“…<b>Conclusions:</b> This study introduces a deep learning framework for the automatic segmentation of lung regions in CT images, leveraging an articulated pipeline and demonstrating excellent performance of the model, effectively isolating lung regions while excluding confounding anatomical structures. …”
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IncSAR: A Dual Fusion Incremental Learning Framework for SAR Target Recognition by George Karantaidis, Athanasios Pantsios, Ioannis Kompatsiaris, Symeon Papadopoulos

“…In this paper, we introduce IncSAR, an incremental learning framework designed to tackle catastrophic forgetting in SAR target recognition. …”
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A Framework for Early Detection of Glaucoma in Retinal Fundus Images Using Deep Learning by Murali Govindan, Vinod Kumar Dhakshnamurthy, Kannan Sreerangan, Manikanda Devarajan Nagarajan, Suresh Kumar Rajamanickam

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FAViTNet: An Effective Deep Learning Framework for Non-Invasive Fetal Arrhythmia Diagnosis by Bipin Samuel, Malaya Kumar Hota

“…This study intends to develop a framework for the effective discernment of fetal arrhythmia that assists obstetricians in diagnosing whether the fetuses have any abnormality in cardiac rhythm. …”
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Cancelable Multi-Branch Deep Learning Framework for Privacy-Preserving ECG Biometric Authentication by Mohamed Hammad, Ali Abdullah S. AlQahtani, Mohammed ELAffendi, Abdelhamied A. Ateya, Nebojsa Bacanin

“…This paper presents a novel cancelable ECG biometric authentication framework that integrates a Cancelable Dynamic Biometric Transformation (CDBT) with a multi-branch deep learning architecture to enhance both privacy and performance. …”
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Development of ANPR Framework for Pakistani Vehicle Number Plates Using Object Detection and OCR by Salma, Maham Saeed, Rauf ur Rahim, Muhammad Gufran Khan, Adil Zulfiqar, Muhammad Tahir Bhatti

“…The obtained mAP score of the YOLOv3 is 94.3% and the YOLOv4 model is 99.5% on the 0.50 threshold, whereas the average accuracy score of our framework is found to be 73%. For comparison and validation, we implemented a LeNet Convolutional Neural Network (CNN) architecture which uses the segmented image as an input. …”
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DeepSpoofNet: a framework for securing UAVs against GPS spoofing attacks by Aziz Ur Rehman Badar, Danish Mahmood, Adeel Iqbal, Sung Won Kim, Sedat Akleylek, Korhan Cengiz, Ali Nauman

“…These include imbalanced datasets, sub-optimal feature selection, and the accuracy of attack detection in resource-constrained environments. The proposed framework investigates the optimal pairing of feature selection (FS) methodologies and deep learning techniques for detecting GPS spoofing attacks on UAVs. …”
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