Caste, Constitution, Court, Equality: The Social Justice Imbroglio in Contemporary India by Ishita Banerjee-Dube

“…This article addresses these issues by revisiting the convoluted trajectory of positive discrimination (termed “reservation”) in India as an illustrative and instructive example. …”
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Combined label matrix with the conditional generative adversarial network for secret image restoration by Jianzhong Yang, Xianquan Zhang, Chunqiang Yu, Guoxiang Li, Zhenjun Tang

“…Because the noise in a corrupted secret image is very special, the existing denoising algorithms have difficulty directly restoring the corrupted secret image well. …”
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Classification of Lung Nodule Using Hybridized Deep Feature Technique by Malin Bruntha, Immanuel Alex Pandian, Siril Sam Abraham

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NFT Cryptopunk Generation Using Machine Learning Algorithm (DCGAN) by Pooja Singhal, Deepak Aneja, Musaed Alhussein, Ritu Gupta, Khursheed Aurangzeb, Nitish Pathak

“…A non-fungible token (NFT) is a kind of digital asset that signifies ownership or proof of authenticity of a special good or piece of material, such as artwork, music, films, or tweets. …”
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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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Deep Learning for Traffic Scene Understanding: A Review by Parya Dolatyabi, Jacob Regan, Mahdi Khodayar

“…The paper synthesizes insights from a broad range of studies, tracing the evolution from traditional image processing methods to sophisticated DL techniques, such as Convolutional Neural Networks (CNNs) and Generative Adversarial Networks (GANs). …”
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Multi-source data fusion-based knowledge transfer for unmanned aerial vehicle flight data anomaly detection and recovery by Lei Yang, Shaobo Li, Liya Yu, Caichao Zhu, Congbao Wang

“…However, in practice, it is inevitable to face the situation of limited data, such as the high cost of data acquisition and the difficulty of collecting data in special scenarios, resulting in the performance degradation of the traditional data-driven methods with limited samples. …”
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Analysis of the Influence of Image Resolution in Traffic Lane Detection Using the CARLA Simulation Environment by Aron Csato, Florin Mariasiu, Gergely Csiki

“…Computer vision is one of the key technologies of advanced driver assistance systems (ADAS), but the incorporation of a vision-based driver assistance system (still) poses a great challenge due to the special characteristics of the algorithms, the neural network architecture, the constraints, and the strict hardware/software requirements that need to be met. …”
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The Use of Artificial Intelligence in Sturgeon Aquaculture by Dragoș Sebastian Cristea, Alexandru Adrian Gavrilă, Ștefan Mihai Petrea, Dan Munteanu, Sofia David, Cătălin Octavian Mănescu

“…The application challenges were significant, which was determined by the special morphological peculiarities of the sturgeons (shape, way of swimming, their dimensions). …”
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TADNet: A Time and Attention-Based Point Cloud Denoising Network for Autonomous Driving in Adverse Weather by Y. Zhang, H. Huang, X. Yan, Y. Liang, Y. Li, J. Yang

“…The method is based on the 3D-OutDet network with the addition of Convolutional Block Attention Module (CBAM), which highlights important features and suppresses minor ones. …”
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On Classification of the Human Emotions from Facial Thermal Images: A Case Study Based on Machine Learning by Marius Sorin Pavel, Simona Moldovanu, Dorel Aiordachioaie

“…., images with Gaussian noise and images with “salt and pepper” type noise that come from two built-in special databases. An augmentation process was applied to the initial raw images that led to the development of the two databases with added noise, as well as the subsequent augmentation of all images, i.e., rotation, reflection, translation and scaling. (2) Methods: The multiclass classification process was implemented through two subsets of methods, i.e., machine learning with random forest (RF), support vector machines (SVM) and k-nearest neighbor (KNN) algorithms and deep learning with the convolutional neural network (CNN) algorithm. (3) Results: The results obtained in this paper with the two subsets of methods belonging to the field of artificial intelligence (AI), together with the two categories of facial thermal images with added noise used as input, were very good, showing a classification accuracy of over 99% for the two categories of images, and the three corresponding classes for each. (4) Discussion: The augmented databases and the additional configurations of the implemented algorithms seems to have had a positive effect on the final classification results.…”
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Bureaucratic Behavior and Utilization of Online Single Submission (OSS) Technology by Nur Mulyani Sari, Bachtari Alam Hidayat, Rika Destiny Sinaga

“… Bureaucratic behavior in Indonesia is often criticized for being slow, convoluted, and lacking transparency, ultimately reducing investor interest at the regional level. …”
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Differentiating localized autoimmune pancreatitis and pancreatic ductal adenocarcinoma using endoscopic ultrasound images with deep learning by Hitomi Nakamura, Motohisa Fukuda, Akiko Matsuda, Naohiko Makino, Hirohito Kimura, Yu Ohtaki, Yoshihito Nawa, Soushi Oyama, Yuya Suzuki, Toshikazu Kobayashi, Tetsuya Ishizawa, Yasuharu Kakizaki, Yoshiyuki Ueno

“…Hence, we developed a special cross‐validation framework to search for effective methodologies of deep learning in distinguishing autoimmune pancreatitis from pancreatic ductal adenocarcinoma on endoscopic ultrasound images. …”
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Deep Learning-Based Postural Asymmetry Detection Through Pressure Mat by Iker Azurmendi, Manuel Gonzalez, Gustavo García, Ekaitz Zulueta, Elena Martín

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Enhancing corn industry sustainability through deep learning hybrid models for price volatility forecasting. by Chengjin Yang, Yanzhong Zhai, Zehua Liu

“…Secondly, BiTCEN designed in this paper effectively captures the short-term dependencies in the corn price data through the unique bidirectional structure and the special hybrid convolutional structure, and then accurately extracts the local features of the data, while BiLSTM mines the long-term trends and complex dependencies in the data by exploiting its bidirectional processing and long-term memory capabilities. …”
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Attention-Module-Guided Time-Lapse Leakage Plume Imaging Driven by LeakInv-CUNet GPR Inversion Framework by Honghua Wang, Shan Wang, Fei Zhou, Yi Lei, Bin Zhang

“…By leveraging the dual advantages of the Convolutional Block Attention Module (CBAM) and U-Net architecture, the developed LeakInv-CUNet framework effectively extracts subtle leakage-induced response features, enabling refined imaging of leakage plumes and their orientations. …”
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Identification of glass eel capture equipment in the Yangtze River estuary based on high-spatial -resolution imagery and an improved YOLOv8 model by Pengfei Zhu, Weifeng Zhou

“…China's fisheries authorities have adopted a special permit regulation for glass eel capture to control the scale and intensity of these activities. …”
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Diagnosing autism spectrum disorders using a double deep Q-Network framework based on social media footprints by Nesren S. Farhah, Nesren S. Farhah, Ahmed Abdullah Alqarni, Ahmed Abdullah Alqarni, Nadhem Ebrahim, Sultan Ahmad, Sultan Ahmad

“…The dataset was processed to exclude lowercase text and special characters, followed by a tokenization approach to convert the text into integer word sequences. …”
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LiDAR Sensor Parameter Augmentation and Data-Driven Influence Analysis on Deep-Learning-Based People Detection by Lukas Haas, Florian Sanne, Johann Zedelmeier, Subir Das, Thomas Zeh, Matthias Kuba, Florian Bindges, Martin Jakobi, Alexander W. Koch

“…The DNNs PointVoxel-Region-based Convolutional Neural Network (PV-RCNN) and Sparsely Embedded Convolutional Detection (SECOND) both only show a reduction in object detection of less than 5% with a reduced resolution of up to 32 factors, for an increase in distance of 4 factors, and with a Gaussian noise up to <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>μ</mi><mo>=</mo><mn>0</mn></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>σ</mi><mo>=</mo><mn>0.07</mn></mrow></semantics></math></inline-formula>. …”
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Revolutionizing total hip arthroplasty: The role of artificial intelligence and machine learning by Umile Giuseppe Longo, Sergio De Salvatore, Alice Piccolomini, Nathan Samuel Ullman, Giuseppe Salvatore, Margaux D'Hooghe, Maristella Saccomanno, Kristian Samuelsson, Rocco Papalia, Ayoosh Pareek

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