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c2-20020a5b0bc2000000b0066e4a75e5ffmr4165607ybr.642.1657724840759; Wed, 13 Jul 2022 08:07:20 -0700 (PDT) MIME-Version: 1.0 From: mohamed Lahby Date: Wed, 13 Jul 2022 16:08:19 +0100 Message-ID: To: caml-list@inria.fr Content-Type: multipart/alternative; boundary="00000000000044f4eb05e3b12495" Subject: [Caml-list] [Free Springer Book, July 15, 2022 ] Last chance to submit your short abstract: on Applications of Remote Sensing Techniques for Sustainable Security Reply-To: mohamed Lahby X-Loop: caml-list@inria.fr X-Sequence: 18818 Errors-To: caml-list-owner@inria.fr Precedence: list Precedence: bulk Sender: caml-list-request@inria.fr X-no-archive: yes List-Id: List-Help: List-Subscribe: List-Unsubscribe: List-Post: List-Owner: List-Archive: Archived-At: --00000000000044f4eb05e3b12495 Content-Type: text/plain; charset="UTF-8" Content-Transfer-Encoding: quoted-printable - We apologize if you receive multiple copies of this CFC. - We appreciate your help to forward this CFC to your friends & email lists= . *=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D= =3D=3D=3DCall for chapters=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D= =3D=3D=3D=3D=3D* Dear colleagues, We are in the process of coming up with a volume titled *=E2=80=9CApplicati= ons of Remote Sensing Techniques for Sustainable Security =E2=80=9D *to be publ= ished by Springer (proposal is initially communicated, awaiting for final approval) at *the end of 2022.* We cordially invite you to contribute a chapter. The full chapter is due later this year but for now, I will just need the following: - Author List - Chapter Title - Abstract (between 2 and 6 sentences) The last deadline to submit your short abstract directly at lahby@ieee.org is *July 15, 2022 (Firm Deadline)* *SCOPE:* With the advent of the big data era in remote sensing, artificial intelligence (AI) has spread to almost every corner of various remote sensing applications. In many cases, the characteristics of remote sensing big data, such as multi-source, multi-scale, high-dimensional, dynamic state, isomeric, and non-linear features, etc., are well learned by advanced AI algorithms. Data-driven methods, especially deep learning models, have achieved state-of-the-art results for most remote sensing image processing tasks (object detection, segmentation, etc.) and some inverse remote sensing task= s (atmosphere, vegetation, etc.). Using large labeled datasets, we can often make very accurate predictions on remote sensing data. However, current data-driven AI has not provided us with clear physical or cognitive meaning of remote sensing data's internal features and representations. Most deep learning techniques do not reveal how data features take effect and why predictions are made. Remote sensing data has exacerbated the problem of opacity and inexplicability of current AI. It becomes a barrier between the latest AI techniques and some remote sensing applications. Many scientists in hydrological remote sensing, atmospheric remote sensing, oceanic remote sensing, etc. do not even believe the results of deep learning predictions, as these communities are more inclined to believe models with clear physical meaning. This forthcoming book seeks contributions to remote sensing data. In particular, we are looking for research papers on applications of remote sensing in many fields of smart cities such as smart transportation, smart agriculture, and smart Environment. *NB: *There are no submission or acceptance fees for manuscripts submitted to this book for publication The tentative structure of the book (but are not limited to the following Parts) is mentioned below:. *Part 1: Theoretical and Applied Aspects of Remote Sensing* - Chapter 1. Remote Sensing Techniques State-of-the-Art - Chapter 2. Hyperspectral remote sensing applications: State-of-the-Art - Chapter 3. Smart cities: State-of-the-Art *Part 2: Remote sensing and Smart cities Applications* - Chapter 4. Smart Agriculture Security - Chapter 5. Smart Transportation Security - Chapter 6. Smart Environment security - Chapter 7. Smart Buildings security; - Chapter 8. Smart Economy security *Part 3: Remote sensing and technologies* - Chapter 9. Artificial Intelligence for Enabled Remote Sensing - Chapter 10. machine learning for Enabled Remote Sensing - Chapter 11. Deep Learning for Enabled Remote Sensing - Chapter 12. XAI for Enabled Remote Sensing - Chapter 13. Big Data for Enabled Remote Sensing - Chapter 14. Blockchain for Enabled remote sensing *Part 4: Futuristic Ideas* - Chapter 15. Futuristic Ideas for Remote sensing Best regards --00000000000044f4eb05e3b12495 Content-Type: text/html; charset="UTF-8" Content-Transfer-Encoding: quoted-printable

-=C2=A0We apologize if you receive= multiple copies of this=C2=A0CFC.

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=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D= =3D=3D=3D=3D=3DCall for chapters=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D= =3D=3D=3D=3D=3D=3D=3D

Dear colleagues,

We are i= n the process of coming up with a volume titled=C2=A0=E2=80=9CApplicatio= ns of=C2=A0Remote=C2=A0Sensing=C2=A0Techniques for Sustainable Security= =E2=80=9D=C2=A0to be published by Springer (proposal is initially comm= unicated, awaiting for final approval) at=C2=A0t= he end of 2022.

We cordially invite you to contribute a chapter. The full chapte= r is due later this year but for now, I will just need the following:
- = Author List
- Chapter Title
- Abstract (between 2 and 6 sentences)The last deadline to submit your short abstract directly at=C2=A0lahby@ieee.org=C2=A0is= =C2=A0July 15, 2022 (Firm Deadline)
SCOPE:
With the advent of the big data er= a in=C2=A0remote=C2=A0sensing,=C2=A0artificial=C2=A0intelligence=C2=A0(= AI) has spread to almost every corner of various=C2=A0remote=C2=A0sensing=C2=A0applications. In many cases, the characteristics of=C2=A0remote= =C2=A0sensing=C2=A0big data, such as multi-source, multi-scale, high-dime= nsional, dynamic state, isomeric, and non-linear features, etc., are well l= earned by advanced AI algorithms. Data-driven methods, especially deep lear= ning models, have achieved state-of-the-art results for most=C2=A0remote= =C2=A0sensing=C2=A0image processing tasks (object detection, segmentation= , etc.) and some inverse=C2=A0remote=C2=A0sensing=C2=A0tasks (atmospher= e, vegetation, etc.). Using large labeled datasets, we can often make very = accurate predictions on=C2=A0remote=C2=A0sensing=C2=A0data.
However,= current data-driven AI has not provided us with clear physical or cognitiv= e meaning of=C2=A0remote=C2=A0sensing=C2=A0data's internal features= and representations. Most deep learning techniques do not reveal how data = features take effect and why predictions are made.=C2=A0Remote=C2=A0sensing=C2=A0data has exacerbated the problem of opacity and inexplicability o= f current AI. It becomes a barrier between the latest AI techniques and som= e=C2=A0remote=C2=A0sensing=C2=A0applications. Many scientists in hydrol= ogical=C2=A0remote=C2=A0sensing, atmospheric=C2=A0remote=C2=A0sensing, oceanic=C2=A0remote=C2=A0sensing, etc. do not even believe the resu= lts of deep learning predictions, as these communities are more inclined to= believe models with clear physical meaning.=C2=A0
This forthcoming book= seeks contributions to=C2=A0remote=C2=A0sensing=C2=A0data. In particul= ar, we are looking for research papers on=C2=A0applications of=C2=A0remote=C2=A0sensing=C2=A0in many fields of smart cities such as smart transpor= tation, smart agriculture, and smart Environment.

= NB:=C2=A0There are no submission or acceptance fees for manuscripts = submitted to this book for publication

The tentative structure of th= e book (but are not limited to the following Parts) is mentioned below:.

Part 1: Theoretical and Applied Aspect= s of=C2=A0Remote=C2=A0Sensing
  • Chapter 1.=C2=A0Remote=C2=A0Sensing=C2=A0Techniques State-of-the-Art
  • Chapter 2. Hyperspectral=C2=A0remote=C2= =A0se= nsing=C2=A0applications: State-of-the-Art
  • Chapter 3. Smart cities: State-of-the-Art
Part 2:=C2= =A0Re= mote=C2=A0sensing=C2=A0and Smart cities Applications
    Chapter 4. Smart Agriculture Security
  • Chapter 5. Smart Transportation Security
    • Chapter 6. Smart Environment security
  • Chapter 7. Smart Buildings security;
  • Chapter 8. Smart Economy security
Part 3= :=C2=A0Remote=C2=A0sensing=C2=A0and technologies
  • Chapter 9. Artificial Intelligence for Enabled=C2=A0<= span style=3D"color:rgb(60,64,67);background-color:rgb(253,226,147)">Remote= =C2=A0Sensing
  • Chapter 10. machi= ne learning for Enabled=C2=A0Remote=C2=A0Sensing
  • Chapter 11. Deep Learning for Enabled=C2=A0Remote=C2=A0Sensing
  • Chapter 12. XAI for Enabled=C2=A0Remote<= /span>=C2=A0Sensing
  • Chapter 13. Big Da= ta for Enabled=C2=A0Remote=C2=A0Sensing
  • Chapter 14. Blockchain for Enabled=C2=A0remote=C2=A0sensing
    • Part =C2=A04: =C2=A0Futuristic Ideas
    • Chapter 15. Futuristic Ideas for=C2=A0Remote=C2=A0sensing
      • =

<= /div>
Best regards
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