Cognitive computing is a field of computer science that focuses on creating computer systems that can perform tasks that normally require human cognitive abilities, such as natural language processing, pattern recognition, and decision-making. Cognitive computing systems are designed to mimic the way the human brain works, using techniques such as machine learning, deep learning, natural language processing, and computer vision. The goal of cognitive computing is to create intelligent systems that can interact with humans more naturally and intuitively. These systems can be used in a variety of applications, including healthcare, finance, customer service, and education. Cognitive computing is often used in combination with other technologies, such as big data analytics and the Internet of Things (IoT), to create powerful systems that can process large amounts of data and make intelligent decisions in real time.
This Research Topic focuses on Ethical AI and Explainable AI, addressing concerns about responsible AI deployment and the need for transparency. Framework and strategies for ethical consideration in Cognitive computing. XAI to enhance the trust and adoption of cognitive systems. This Research Topic aims to pioneer research and development in cognitive computing, fostering an ecosystem of ethical, explainable, and highly functional AI systems.
This Research Topic will provide a comprehensive platform for researchers, practitioners, and industry experts to present their latest findings and insights into cognitive computing. Cognitive computing has a wide range of applications across different domains. The Research Topic adequately focuses on various applications of cognitive computing, including but not limited to the following:
1. Innovative Approaches and Solutions:
2. Challenges in Cognitive Computing:
3. Applications of Cognitive Computing:
- Healthcare: Cognitive computing enhances healthcare to improve patient care, diagnosis, and treatment. It analyzes patient data to help doctors make better decisions by identifying patterns and trends in medical records.
- Customer service: Cognitive computing can be used in customer service to provide more personalized and efficient support. It can help agents to quickly resolve issues by analyzing customer history and previous interactions.
- Education: Cognitive computing can be used in education to provide personalized learning experiences for students. It can analyze student data and recommend courses or activities tailored to individual learning style.
- Self-driving and transportation: Cognitive computing can enhance transportation safety and efficiency by analyzing sensor and camera data to help self-driving cars respond to their environment.
- Object recognition: Cognitive computing enables machines to recognize and identify objects in their environment. This can be achieved through computer vision and machine learning (ML) methods analysing cameras and sensor data.
- Natural language processing (NLP): Cognitive computing enables machine/robots to understand and respond to human language. This is achieved through NLP algorithms that analyze languages and provide appropriate responses.
- Cognitive Computing (cc) in robotics: By incorporating CC technologies, such as ML and NLP, robots can become more intelligent and responsive to their environment.
- Autonomous navigation: Cognitive computing can be used to navigate autonomously in complex environments. This is achieved through algorithms analyzing sensor data to provide real-time feedback to the navigation system, utilizing computer vision and machine learning. - Personalization: Cognitive computing can be used to personalize the machine interactions with humans based on their individual preferences and behavior.
In nutshell, Cognitive computing transforms our lives by creating intelligent systems that interact naturally with humans to solve problems effectively.
Keywords:
Cognitive computing, Natural language processing (NLP), Computer vision, Human-computer interaction, machine learning (ML), deep learning (DL)
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
Cognitive computing is a field of computer science that focuses on creating computer systems that can perform tasks that normally require human cognitive abilities, such as natural language processing, pattern recognition, and decision-making. Cognitive computing systems are designed to mimic the way the human brain works, using techniques such as machine learning, deep learning, natural language processing, and computer vision. The goal of cognitive computing is to create intelligent systems that can interact with humans more naturally and intuitively. These systems can be used in a variety of applications, including healthcare, finance, customer service, and education. Cognitive computing is often used in combination with other technologies, such as big data analytics and the Internet of Things (IoT), to create powerful systems that can process large amounts of data and make intelligent decisions in real time.
This Research Topic focuses on Ethical AI and Explainable AI, addressing concerns about responsible AI deployment and the need for transparency. Framework and strategies for ethical consideration in Cognitive computing. XAI to enhance the trust and adoption of cognitive systems. This Research Topic aims to pioneer research and development in cognitive computing, fostering an ecosystem of ethical, explainable, and highly functional AI systems.
This Research Topic will provide a comprehensive platform for researchers, practitioners, and industry experts to present their latest findings and insights into cognitive computing. Cognitive computing has a wide range of applications across different domains. The Research Topic adequately focuses on various applications of cognitive computing, including but not limited to the following:
1. Innovative Approaches and Solutions:
2. Challenges in Cognitive Computing:
3. Applications of Cognitive Computing:
- Healthcare: Cognitive computing enhances healthcare to improve patient care, diagnosis, and treatment. It analyzes patient data to help doctors make better decisions by identifying patterns and trends in medical records.
- Customer service: Cognitive computing can be used in customer service to provide more personalized and efficient support. It can help agents to quickly resolve issues by analyzing customer history and previous interactions.
- Education: Cognitive computing can be used in education to provide personalized learning experiences for students. It can analyze student data and recommend courses or activities tailored to individual learning style.
- Self-driving and transportation: Cognitive computing can enhance transportation safety and efficiency by analyzing sensor and camera data to help self-driving cars respond to their environment.
- Object recognition: Cognitive computing enables machines to recognize and identify objects in their environment. This can be achieved through computer vision and machine learning (ML) methods analysing cameras and sensor data.
- Natural language processing (NLP): Cognitive computing enables machine/robots to understand and respond to human language. This is achieved through NLP algorithms that analyze languages and provide appropriate responses.
- Cognitive Computing (cc) in robotics: By incorporating CC technologies, such as ML and NLP, robots can become more intelligent and responsive to their environment.
- Autonomous navigation: Cognitive computing can be used to navigate autonomously in complex environments. This is achieved through algorithms analyzing sensor data to provide real-time feedback to the navigation system, utilizing computer vision and machine learning. - Personalization: Cognitive computing can be used to personalize the machine interactions with humans based on their individual preferences and behavior.
In nutshell, Cognitive computing transforms our lives by creating intelligent systems that interact naturally with humans to solve problems effectively.
Keywords:
Cognitive computing, Natural language processing (NLP), Computer vision, Human-computer interaction, machine learning (ML), deep learning (DL)
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.