Enhanced SSD with interactive multi-scale attention features for object detection

Zhou, Shuren; Qiu, Jia

doi:10.1007/s11042-020-10191-2

Cited by 45 publications

(29 citation statements)

References 33 publications

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“…The general chemical formula for HIPs is ABX 3 , where A is a monovalent inorganic cation, similar to Cs + : cesium; X is a halogen anion including F − , I − , Br − , and Cl − , and B is a divalent metallic cation such as Pb 2+ , Sn 2+ , Cu 2+ , etc. [29][30][31][32][33][34][35][36][37][38][39][40][41][42]. Inorganic hybrid perovskites have a semiconducting nature.…”

Section: Introductionmentioning

confidence: 99%

RETRACTED: The Effect of Structural Phase Transitions on Electronic and Optical Properties of CsPbI3 Pure Inorganic Perovskites

et al. 2021

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Hybrid inorganic perovskites (HIPs) have been developed in recent years as new high-efficiency semiconductors with a wide range of uses in various optoelectronic applications such as solar cells and light-emitting diodes (LEDs). In this work, we used a first-principles theoretical study to investigate the effects of phase transition on the electronic and optical properties of CsPbI3 pure inorganic perovskites. The results showed that at temperatures over 300 °C, the structure of CsPbI3 exhibits a cube phase (pm3m) with no tilt of PbI6 octahedra (distortion index = 0 and bond angle variance = 0). As the temperature decreases (approximately to room temperature), the PbI6 octahedra is tilted, and the distortion index and bond angle variance increase. Around room temperature, the CsPbI3 structure enters an orthorhombic phase with two tilts PbI6 octahedra. It was found that changing the halogens in all structures reduces the volume of PbI6 octahedra. The tilted PbI6 octahedra causes the distribution of interactions to vary drastically, which leads to a change in band gap energy. This is the main reason for the red and blue shifts in the absorption spectrum of CsPbI3. In general, it can be said that the origin of all changes in the structural, electronic, and optical properties of HIPs is the changes in the volume, orientation, and distortion index of PbI6 octahedra.

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Section: Introductionmentioning

confidence: 99%

RETRACTED: The Effect of Structural Phase Transitions on Electronic and Optical Properties of CsPbI3 Pure Inorganic Perovskites

et al. 2021

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“…ML techniques have achieved great success in image recognition field such as medical image classification [ 15 ], object detection [ 16 ], face recognition [ 17 ], traffic sign classification, etc. [ 18 ].…”

Section: In Microorganisms Image Recognitionmentioning

confidence: 99%

Machine Learning and Deep Learning Based Computational Approaches in Automatic Microorganisms Image Recognition: Methodologies, Challenges, and Developments

Rani

Kotwal

Manhas

et al. 2021

Arch Computat Methods Eng

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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.

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“…The most common heat exchangers are car radiators and radiators [4][5][6]. Heat exchangers are used in various industries such as air conditioning [7][8][9][10][11], automobile, oil and gas, and many other industries [6,12,13]. Heating equipment in process systems such as refineries is generally divided into two general categories of furnaces and heat exchangers [14][15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Use of Organic and Copper-Based Nanoparticles on the Turbulator Installment in a Shell Tube Heat Exchanger: A CFD-Based Simulation Approach by Using Nanofluids

Chupradit

Jalil

Enina

et al. 2021

Journal of Nanomaterials

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Heat exchangers with unique specifications are administered in the food industry, which has expanded its sphere of influence even to the automotive industry due to this feature. It has been used for convenient maintenance and much easier cleaning. In this study, two different nanomaterials, such as Cu-based nanoparticles and an organic nanoparticle of Chloro-difluoromethane (R22), were used as nanofluids to enhance the efficiency of heat transfer in a turbulator. It is simulated by computational fluid dynamics software (Ansys-Fluent) to evaluate the Nusselt number versus Reynolds number for different variables. These variables are diameter ratio, torsion pitch ratio, and two different nanofluids through the shell tube heat exchanger. It is evident that for higher diameter ratios, the Nusselt number has been increased significantly in higher Reynolds numbers as the heat transfer has been increased in turbulators. For organic fluids (R22), the Nusselt number has been increased significantly in higher Reynolds numbers as the heat transfer has been increased in turbulators due to the proximity of heat transfer charges. At higher torsion pitch ratios, the Nusselt number has been increased significantly in the higher Reynolds number as the heat transfer has been increased in turbulators, especially in higher velocities and pipe turbulence torsions.

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Enhanced SSD with interactive multi-scale attention features for object detection

Cited by 45 publications

References 33 publications

RETRACTED: The Effect of Structural Phase Transitions on Electronic and Optical Properties of CsPbI3 Pure Inorganic Perovskites

RETRACTED: The Effect of Structural Phase Transitions on Electronic and Optical Properties of CsPbI3 Pure Inorganic Perovskites

Machine Learning and Deep Learning Based Computational Approaches in Automatic Microorganisms Image Recognition: Methodologies, Challenges, and Developments

Use of Organic and Copper-Based Nanoparticles on the Turbulator Installment in a Shell Tube Heat Exchanger: A CFD-Based Simulation Approach by Using Nanofluids

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