[Intelligenza Artificiale] The official repo for the paper: "CLAM: A Synergistic Deep Learning Model for Multi-Step Stock Price Trend Forecasting".

This research presents a hybrid deep learning framework combining MobileNet V2 with LSTM, GRU, and Bidirectional LSTM for classifying various potato diseases. The study explores the performance of different architectures to determine the optimal configuration for accurate disease categorization.

Welcome to the GitHub repository for the project titled "Power-Law Based Speech Command Recognition using Hybrid CNN-GRU Model." This repository focuses on advancing speech command recognition in noisy conditions by employing a Power-Normalized Cepstral Coefficient (PNCC) implementation.

This work was supported in part by the MOTIE (Ministry of Trade, Industry & Energy), Republic of Korea, under the Technology Innovation Program, and in part by the MSIT (Ministry of Science and ICT), Republic of Korea, under the Grand ICT Research Center Support Program.For full details, refer the published journal article using the link below.

An IoT-enabled decision support system for Sri Lankan small-scale fishermen - featuring a Flutter mobile app, ESP32 onboard device with GPS/EEZ monitoring, hybrid spatio-temporal ML fishing zone prediction, Node.js/MongoDB backend, and a React web control center.

This repository contains stock datasets of Target (TGT), Amazon (AMZN), and Walmart (WMT). It also includes the source code of our Hybrid Deep Learning model (CNN-BiLSTM-GRU) with the implementation of Phase Space Reconstruction technique.