In the rapidly evolving field of machine learning engineering, access to large, high-quality, and well-balanced labeled datasets is indispensable for accurate product classification. This necessity holds particular significance in sectors such as the ceramics industry, in which effective production line activities are paramount and deep learning classification mechanisms are particularly relevant for streamlini...
This work explores the classification of driving behaviors using a hybrid deep learning model that combines Convolutional Neural Networks (CNNs) with Long Short-Term Memory (LSTM) networks (ConvLSTM). Sensor data are collected from a smartphone application and undergo a preprocessing pipeline, including data normalization, labeling, and feature extraction, to enhance the model’s performance. By capturing tempor...
Traditional police interrogation processes remain largely time-consuming and reliant on substantial human effort for both analysis and documentation. Intuition Artificial Intelligence (INTU-AI) is a Windows application designed to digitalize the administrative workflow associated with police interrogations, while enhancing procedural efficiency through the integration of AI-driven emotion recognition models. Th...
Natural stone has long been used in construction, as its properties provide functional and visual value, and the natural stone market currently holds significant importance in the global economy. It is important to consider integrating new technologies in the production chain to aid the industry in moving forward, increasing profit margins and reducing wasted material. This article reviews recent trends in usin...
Rising global fire incidents necessitate effective solutions, with forest surveillance emerging as a crucial strategy. This paper proposes a complete solution using technology that integrates visible and infrared spectrum images through Unmanned Aerial Vehicles (UAVs) for enhanced detection of people and vehicles in forest environments. Unlike existing computer vision models relying on single-sensor imagery, th...
Emotion recognition has become increasingly important in the field of Deep Learning (DL) and computer vision due to its broad applicability by using human–computer interaction (HCI) in areas such as psychology, healthcare, and entertainment. In this paper, we conduct a systematic review of facial and pose emotion recognition using DL and computer vision, analyzing and evaluating 77 papers from different sources...
Piano notes recognition, or pitch estimation of piano notes has been a popular research topic for many years, and is still investigated nowadays. It is a fundamental task during the process of automatic music transcription (extracting the musical score from an acoustic signal). We take advantage of Cartesian Genetic Programming (CGP) to evolve mathematical functions that act as independent classifiers for piano...
This paper presents and describes CGP4Matlab, a powerful toolbox that allows to run Cartesian Genetic Programming within MATLAB. This toolbox is particularly suited for signal processing and image processing problems. The implementation of CGP4Matlab, which can be freely downloaded, is described. Some encouraging results on the problem of pitch estimation of musical piano notes achieved using this toolbox are a...
Pitch Estimation, also known as Fundamental Frequency (F0) estimation, has been a popular research topic for many years, and is still investigated nowadays. This paper presents a novel approach to the problem of Pitch Estimation, using Cartesian Genetic Programming (CGP). We take advantage of evolutionary algorithms, in particular CGP, to evolve mathematical functions that act as classifiers. These classifiers ...