We present a new image compression paradigm to achieve "intelligently coding for machine" by cleverly leveraging the common sense of Large Multimodal Models (LMMs). We are motivated by the evidence that larg...
详细信息
ISBN:
(纸本)9798331529543;9798331529550
We present a new image compression paradigm to achieve "intelligently coding for machine" by cleverly leveraging the common sense of Large Multimodal Models (LMMs). We are motivated by the evidence that large language/multimodal models are powerful general-purpose semantics predictors for understanding the real world. Different from traditional image compression typically optimized for human eyes, the image coding for machines (ICM) framework we focus on requires the compressed bitstream to more comply with different downstream intelligent analysis tasks. To this end, we employ LMM to tell codec what to compress: 1) first utilize the powerful semantic understanding capability of LMMs w.r.t object grounding, identification, and importance ranking via prompts, to disentangle image content before compression, 2) and then based on these semantic priors we accordingly encode and transmit objects of the image in order with a structured bitstream. In this way, diverse vision benchmarks including image classification, object detection, instance segmentation, etc., can be well supported with such a semantically structured bitstream. We dub our method "SDComp" for "Semantically Disentangled Compression", and compare it with state-of-the-art codecs on a wide variety of different vision tasks. SDComp codec leads to more flexible reconstruction results, promised decoded visual quality, and a more generic/satisfactory intelligent task-supporting ability.
A collection of informationtechnology (IT) services known as "cloud computing" is offered to customers across a network on a subscription basis with the flexibility to scale up or down based on their servic...
详细信息
ISBN:
(纸本)9781665475785
A collection of informationtechnology (IT) services known as "cloud computing" is offered to customers across a network on a subscription basis with the flexibility to scale up or down based on their service needs. The emergence of cloud computingtechnology, which has tremendous advantages, is one of the major advancements in recent times. Many computers and servers are specifically devoted to meeting the demands of businesses in a cloud computing system for internal communications. Users can access their services via an internet connection. Registered users have remote access to both hardware and software, thanks to the cloud service, which has made essential adjustments to how information is stored and made accessible. This paper investigates the use of Amazon Web Services (AWS) for big data processing and analytics in South Korea. We collected several domestic journal and conference papers that studied local cloud services based on AWS to introduce distributed systems and cloud computing technologies. This study can provide researchers with a compact version of the extensive AWS-based data processing literature and potential future insights. It can also provide stakeholders tailored services, information about cutting-edge solutions that can influence academics, and details about current research needs.
The recent world advancement in technology especially in the use of IoT devices has posed some serious complications in terms of how effectively we can convey data, this is normally a result of the limited bandwidth a...
详细信息
Quantum information Science (QIS) is potentially a game-changing technology for the future military operational environment. Being significantly dependent on the capabilities of current quantum computers, it is still ...
详细信息
ISBN:
(纸本)9798350343854
Quantum information Science (QIS) is potentially a game-changing technology for the future military operational environment. Being significantly dependent on the capabilities of current quantum computers, it is still very immature;however, evolving rapidly and increasing the technical and knowledge potential of industrial and state actor players that invest in it. Investing in this technology can lead the NATO Alliance to gain quantum superiority and outperform its adversaries in technological development in diverse military domains. This article presents possible applications of QIS in the military domain in the form of use cases. We have formulated these use cases after analysis of today's capabilities of quantum computingtechnology and its prospects for the future of the quantum information domain. Our article concludes with initial recommendations for the early adoption of quantum technology. This paper was presented at the NATO Science and technology Organization Symposium (ICMCIS) organized by the information Systems technology (IST) Panel, IST-200 RSY - the ICMCIS, held in Skopje, North Macedonia, 16-17 May 2023.
As unmanned aerial vehicles (UAVs) demonstrate significant potential for edge computing, their capacity to rapidly deploy computing services at user locations offers considerable advantages. However, their limited ope...
详细信息
Recent work in offline reinforcement learning (RL) has demonstrated the effectiveness of formulating decision-making as return-conditioned supervised learning. Notably, the decision transformer (DT) architecture has s...
详细信息
ISBN:
(纸本)9798350377712;9798350377705
Recent work in offline reinforcement learning (RL) has demonstrated the effectiveness of formulating decision-making as return-conditioned supervised learning. Notably, the decision transformer (DT) architecture has shown promise across various domains. However, despite its initial success, DTs have underperformed on several challenging datasets in goal-conditioned RL. This limitation stems from the inefficiency of return conditioning for guiding policy learning, particularly in unstructured and suboptimal datasets, resulting in DTs failing to effectively learn temporal compositionality. Moreover, this problem might be further exacerbated in long-horizon sparse-reward tasks. To address this challenge, we propose the Predictive coding for Decision Transformer (PCDT) framework, which leverages generalized future conditioning to enhance DT methods. PCDT utilizes an architecture that extends the DT framework, conditioned on predictive codings, enabling decision-making based on both past and future factors, thereby improving generalization. Through extensive experiments on eight datasets from the AntMaze and FrankaKitchen environments, our proposed method achieves performance on par with or surpassing existing popular value-based and transformer-based methods in offline goal-conditioned RL. Furthermore, we also evaluate our method on a goal-reaching task with a physical robot.
The advancement of computer technology has led to the adoption of new management models by schools, improving management efficiency, and a shift from digital to smart campus construction. A crucial phase in the creati...
详细信息
The advancement of computer technology has led to the adoption of new management models by schools, improving management efficiency, and a shift from digital to smart campus construction. A crucial phase in the creation of campus information is the digital campus. There have been several successes in the creation of India smart campuses. India education system has benefited considerably from the contributions of numerous scientists, technologists, educators, and pertinent national policies. As a result, the country's educational system now uses far more informationtechnology. The creation of new smart campuses is crucial to India educational landscape as we approach the era of big data, cloud computing, and artificial intelligence. This article first explains cloud computing and related technologies, then examines the NEC smart campus service platform. Using this information as a foundation, it develops a cloud computing-based smart campus service platform that will aid in the growth of smart campuses in India.
The prosperity of cloud services stimulates the study of reversible data hiding in encrypted images, for which researchers dedicate to find better methods to adopt the new assumption that the ones who provide the cove...
详细信息
ISBN:
(纸本)9783031054914;9783031054907
The prosperity of cloud services stimulates the study of reversible data hiding in encrypted images, for which researchers dedicate to find better methods to adopt the new assumption that the ones who provide the cover images, a.k.a. the Content-owner, are no longer the same as the ones who hide the secret message into them, a.k.a. the Data-hider, and the Data-hider might not always be allowed to know the actual content of cover image the Content-owner provided, while the one who receives the stego image must be able to restore the exact cover image after extracting the secret. A method of such reversible data hiding in encrypted images has been proposed and we propose improvements to enhance its performance and make it more generalized and stable. Experimental results show that our proposal improves its performance even in the worst-case scenario.
Deep Neural Networks are rapidly attracting widespread attention as a key technology for AI applications in 5G era. However, running DNN-based computation tasks on mobile devices is challenging due to limited computat...
详细信息
Fog computing offers advantages like low latency and distributed processing at the network edge. Resource discovery in heterogeneous and distributed fog nodes remain a critical research problem. While traditional appr...
详细信息
暂无评论