A5049386377- Scheduling and Timetabling Solutions
- Metaheuristic Optimization Algorithms Research
- Constraint Satisfaction and Optimization
- Optimization and Packing Problems
- Advanced Manufacturing and Logistics Optimization
- Scheduling and Optimization Algorithms
- Vehicle Routing Optimization Methods
- Evolutionary Algorithms and Applications
- Advanced Multi-Objective Optimization Algorithms
- Data Management and Algorithms
- Manufacturing Process and Optimization
- AI in cancer detection
- Human Pose and Action Recognition
- Assembly Line Balancing Optimization
- Multimodal Machine Learning Applications
- Anomaly Detection Techniques and Applications
- Image Retrieval and Classification Techniques
- Video Surveillance and Tracking Methods
- Neural Networks and Applications
- Optimization and Search Problems
- Advanced Image and Video Retrieval Techniques
- Video Analysis and Summarization
- Gene expression and cancer classification
- Digital Transformation in Industry
- Intelligent Tutoring Systems and Adaptive Learning
Tecnológico de Monterrey
2016-2025
Universidad de Granada
2018
Intel (United States)
2013
Instituto Tecnológico de León
2012
Regarding safety and security, felonies crimes with physical violence remain a significant problem worldwide. Some solutions for pedestrian are guards, police car patrolling, sensors, security cameras. Nonetheless, these methods react only when the crime takes place. In worst cases, damage may be irreversible it has already occurred. Therefore, numerous based on Artificial Intelligence have been proposed to solve this problem. Many approaches detect violent behavior action recognition rely...
The rapid integration of computational thinking (CT) into STEM education highlights its importance as a critical skill for problem-solving in the digital age, equipping students with cognitive tools needed to address complex challenges systematically. This study evaluates CT skills among Engineering and Computer Science using multi-method approach by combining quantitative methods (CTT scores CTS responses) qualitative (thematic analysis open-ended questions), integrating objective...
Job Shop Scheduling problems (JSSPs) have become increasingly popular due to their application in supply chain systems. Several solution approaches appeared the literature. One of them is use low-level heuristics. These methods approximate a but only work well on some kind problems. Hence, combining may improve performance. In this paper, we classical stochastic local optimization algorithm Simulated Annealing train selection hyper-heuristic for solving JSSPs. To do so, an instance generator...
Metaheuristics have become a widely used approach for solving variety of practical problems. The literature is full diverse metaheuristics based on outstanding ideas and with proven excellent capabilities. Nonetheless, oftentimes claim novelty when they are just recombining elements from other methods. Hence, the need standard metaheuristic model vital to stop current frenetic tendency proposing methods chiefly their inspirational source. This work introduces first step generalised...
Deep neural networks have been able to outperform humans in some cases like image recognition and classification. However, with the emergence of various novel categories, ability continuously widen learning capability such from limited samples, still remains a challenge. Techniques Meta-Learning and/or few-shot showed promising results, where they can learn or generalize category/task based on prior knowledge. In this paper, we perform study existing meta-learning techniques computer vision...
Support vector machines (SVMs) are one of the most powerful learning algorithms for solving classification problems. However, in their original formulation, they only deal with binary classification. Traditional extensions SVMs multiclass problems based either on decomposing problem into a number problems, which then independently solved, or reformulating objective function by larger optimization In this paper, we propose MC <sup xmlns:mml="http://www.w3.org/1998/Math/MathML"...
The assessment of strengths and weaknesses a solver is often limited by the diversity cases where it tested upon. As such, paramount to have versatile tool which finds problem instances such excels/fails. In this manuscript, we propose use an evolutionary algorithm for creating tool. To validate our approach, conducted several tests on four heuristics knapsack problem. Although, process can be extended other domains with relatively few changes. cover different sets instances, both favoring...