Zanim poznałem Memmo, moje notatki były rozrzucone po PDF-ach. Teraz obszar roboczy zbiera wszystko w jednym miejscu — widzę dokładnie, co jeszcze muszę powtórzyć.
Machine Vision systems combine image processing with industrial automation. One of the primary areas of application of Machine Vision in the Industry is in the area of Quality Control. Machine vision provides fast, economic and reliable inspection that improves quality as well as business productivity. Building machine vision applications is a challenging task as each application is unique, with its own requirements and desired outcome.
A Guide to Machine Vision in Quality Control follows a practitioner’s approach to learning machine vision. The book provides guidance on how to build machine vision systems for quality inspections. Practical applications from the Industry have been discussed to provide a good understanding of usage of machine vision for quality control. Real-world case studies have been used to explain the process of building machine vision solutions.
The book offers comprehensive coverage of the essential topics, that includes:
The book can be used by students and academics, as well as by industry professionals, to understand the fundamentals of machine vision. Updates to the on-going technological innovations have been provided with a discussion on emerging trends in machine vision and smart factories of the future.
Sheila Anand is a PhD graduate and Professor at Rajalakshmi Engineering College, Chennai, India. She has over three decades of experience in teaching, consultancy and research. She has worked in the software industry and has extensive experience in development of software applications and in systems audit of financial, manufacturing and trading organizations. She guides Ph.D. aspirants and many of her research scholars have since been awarded their doctoral degree. She has published many papers in national and international journals and is a reviewer for several journals of repute.
L Priya is a PhD graduate working as Associate Professor and Head, Department of Information Technology at Rajalakshmi Engineering College, Chennai, India. She has nearly two decades of teaching experience and good exposure to consultancy and research. She has delivered many invited talks, presented papers and won several paper awards in International Conferences. She has published several papers in International journals and is a reviewer for SCI indexed journals. Her areas of interest include Machine Vision, Wireless Communication and Machine Learning.
Zanim poznałem Memmo, moje notatki były rozrzucone po PDF-ach. Teraz obszar roboczy zbiera wszystko w jednym miejscu — widzę dokładnie, co jeszcze muszę powtórzyć.
Podsumowania Memmo to złoto przed egzaminami. Nie muszę czytać 800 stron dwa tygodnie wcześniej — tylko to, co najważniejsze.
Czat AI uratował mnie niejeden raz w noc przed egzaminem. Pytam, dopóki nie zrozumiem — i nie muszę czekać na odpowiedź od grupy studyjnej.
Quizy trafiają w punkt, jeśli chodzi o to, co muszę wiedzieć. Memmo śledzi, na czym się zacinam — więc ćwiczę tylko to, co naprawdę się liczy.
Fiszki z powtórkami rozłożonymi w czasie to magia. Memmo wie, kiedy mam coś zapomnieć i przypomina mi o tym.
Podcasty AI to mój faworyt. Słucham w drodze do szkoły i powtarzam materiał, nie siedząc przed komputerem.
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