Microorganisms or microbes comprise majority of the diversity on earth and are extremely important to human life. They are also integral to processes in the ecosystem. The process of their recognition is highly tedious, but very much essential in microbiology to carry out different experimentation. To overcome certain challenges, machine learning techniques assist microbiologists in automating the entire process. This paper presents a systematic review of research done using machine learning (ML) and deep leaning techniques in image recognition of different microorganisms. This review investigates certain research questions to analyze the studies concerning image pre-processing, feature extraction, classification techniques, evaluation measures, methodological limitations and technical development over a period of time. In addition to this, this paper also addresses the certain challenges faced by researchers in this field. Total of 100 research publications in the chronological order of their appearance have been considered for the time period 1995–2021. This review will be extremely beneficial to the researchers due to the detailed analysis of different methodologies and comprehensive overview of effectiveness of different ML techniques being applied in microorganism image recognition field.

Bacteria are important in a variety of practical domains, including industry, agriculture, medicine etc. A very few species of bacteria are favourable to humans. Whereas, majority of them are extremely dangerous and causes variety of life threatening illness to different living organisms. Traditionally, this class of microbes is detected and classified using different approaches like gram staining, biochemical testing, motility testing etc. However with the availability of large amount of data and technical advances in the field of medical and computer science, the machine learning methods have been widely used and have shown tremendous performance in automatic detection of bacteria. The inclusion of latest technology employing different Artificial Intelligence techniques are greatly assisting microbiologist in solving extremely complex problems in this domain. This paper presents a review of the literature on various machine learning approaches that have been used to classify bacteria, for the period 1998–2020. The resources include research papers and book chapters from different publishers of national and international repute such as Elsevier, Springer, IEEE, PLOS, etc. The study carried out a detailed and critical analysis of penetrating different Machine learning methodologies in the field of bacterial classification along with their limitations and future scope. In addition, different opportunities and challenges in implementing these techniques in the concerned field are also presented to provide a deep insight to the researchers working in this field.

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Abstract-With rapid changes in technology and its increased use in different organizations, the cybercrime and digital forensics methods are also making advancement in new ways to tackle the latest trends in cyber crime. Cybercrime refers to any crime that involves a computer network or any public or private system. Cyber crime is emerging as a serious threat worldwide. The government organizations, police departments and various intelligence units of different countries have started to act accordingly. To control and investigate cybercrime, the investigators use various Digital forensics methods and mechanisms. Digital forensics is the procedure of investigating computer crimes in cyber world. Many researchers have been done a lot in this area to help forensic investigators to resolve the existing challenges with different methodologies designed by them. Experts provided with different tools and technologies to resolve the threats related to cyber crime in a more efficient and speedy manner with minimum loss to the victim. Still the desired technologies and tools are not that much efficient that they can control the occurrence of different types of cyber crime activities. This paper reviews the complete details regarding the growth of cybercrime and its various modes of occurrence at different level. Authors in this paper tries to bring few facts and figures which would be an eye-opener for computer and internet users. Therefore, the current manuscript provides the understanding of various types of cyber crimes and its impact on different section of the society.

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