Titlebook: Intelligent Systems Design and Applications; Deep Learning, Volum Ajith Abraham,Anu Bajaj,Tzung-Pei Hong Conference proceedings 2024 The Ed

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Machine Learning Approaches for Investing Strategies in Stock Market,ine learning techniques utilized for making informed investment strategies in the stock market, with a specific focus on identifying the opportune moments to invest. Novel algorithms like Reinforcement Learning, Gradient Boosting Machines (GBM), Random Forest, Support Vector Machines (SVM), and Long

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OP-FedELM: One-Pass Privacy-Preserving Federated Classification via Evolving Clustering Method and ention due to its decentralized, distributed training and the potential to protect privacy. However, FL presents challenges like privacy concerns, network, and data heterogeneity. This motivated us to propose a two-phase, one-pass FL algorithm, where (I) In the first phase, the differentially privat

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,Gamma Corrected Pyramid Pix2pix – Breast Cancer HE to IHC Image Generation,mammography is the most widely used test. HE (Hematoxylin and Eosin) stained histological analysis, on the other hand, is required to determine the malignancy of the tumor since it analyzes the image at the cellular level. However, Human pidermal Growth Factor Receptor 2 (HER2) expression is critica

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Unveiling Deepfakes: Convolutional Neural Networks for Detection,ument, we present a deepfake detection method that utilizes a convolutional neural network (CNN). Our proposed approach harnesses the power of CNNs to automatically learn features from visual data. To train our CNN model, we use a dataset consisting of even-numbered and odd-numbered images. Even-num

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The Nasdaq Composite Index Prediction Using LSTM and Bi-LSTM Multivariate Deep Learning Approaches,et capitalization-weighted system and runs under a market value-weighted system. Notably, the individual market value of each stock is factored into the calculation of this index. Companies having headquarters both in the United States and elsewhere in the world are included in the index‘s coverage.

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PlastOcean: Detecting Floating Marine Macro Litter (FMML) Using Deep Learning Models,entify and quantify floating plastic ocean patches using satellite images. These techniques can help in making ocean cleanup efforts more targeted and efficient. Today, most institutions working on ocean cleanup, use Manta Trawls for quantifying and manually sampling the plastic garbage patches in t

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